Objective To investigate the relationship between serum glial fibrillary acidic protein(GFAP)level and transcranial Doppler(TCD)parameters in carotid stenosis patients after carotid stent implantation.Methods A total of 123 patients with carotid stenosis who received carotid stent implantation in our hospital from September 2021 to February 2024 were recruited,and di-vided into a normal group(39 cases)and a damaged group(84 cases)according to their cerebro-vascular reserve.The GFAP level and TCD parameters were collected before and after treatment.ROC curve analysis was employed to analyze the value of GFAP level in evaluating cerebrovascu-lar reserve in the patients.Results Significantly larger proportion of diabetes and higher level of total cholesterol were observed in the damaged group than the normal group(P＜0.05).Mean flow velocity(MFV),pulse index(PI),peak systolic velocity(PSV),and levels of GFAP,neuron-specific enolase(NSE)and S-100β were all obviously decreased in both groups after surgery than the levels before(P＜0.05).When compared with the normal group,the damaged group had nota-bly higher serum GFAP level before operation,and lower PI and PSV values and higher GFAP,NSE and S-100β levels after operation(P＜0.05,P＜0.01).Both pre-and post-operative serum GFAP levels were negatively correlated with postoperative MFV,PI and PSV(P＜0.01).The concomitant diabetes,pre-and post-operative serum GFAP levels,and postoperative PSV value and NSE and S-100β levels were independent influencing factors for cerebrovascular reserve in ca-rotid stenosis patients after carotid stent implantation(P＜0.05,P＜0.01).The post-operative se-rum GFAP level showed significantly better value than the pre-operative level in assessing cere-brovascular reserve,with an AUC value of 0.860(95％CI:0.786-0.916)and 0.777(95％CI:0.693-0.847),respectively.Conclusion Serum GFAP level is related to TCD parameters in ca-rotid stenosis patients after carotid stent implantation.Combined GFAP level and TCD parameters together can be used to evaluate the cerebrovascular reserve for the patients.

Objective To explore the mechanism by which the sanguis draconis flavones(SDF)regulates the reactive oxygen species(ROS)/thioredoxin-interacting protein(TXNIP)pathway to mediate cell pyroptosis and improve cerebral ischemia-reperfusion injury(CIRI)in rats.Methods The experimental rats were randomly divided into the control group(Ctrl),the CIRI group,the low-dose SDF group(SDF-L),the high-dose SDF group(SDF-H),and the SDF-H+ROS/TXNIP pathway activator,trimethylamine oxide(TMAO)group(SDF-H+TMAO).Among them,except for the control group,the remaining rats all needed to establish the CIRI rat model by the modified suture method.Zea Longa scoring was performed on rats from each group.ELISA was used to detect the levels of serum inflammatory factors interleukin(IL)-1β,IL-18 and oxidative stress-related factors superoxide dismutase(SOD),malondialdehyde(MDA),glutathione peroxidase(GSH-Px).Flow cytometry was used to measure the ROS levels.Cerebral edema was detected.Cerebral infarction was detected by 2,3,5-triphenyl tetrazolium chloride(TTC)staining.HE staining was used to detect the pathological changes of brain tissue.Immunohistochemistry was used to detect the expression of pyrolytic effector protein dermolin D(GSDMD).Western blotting was used to detect the expression of proteins related to the ROS/TXNIP pathway.Results Compared with the control group,a large area of cerebral infarctions were observed in the brain tissue of the CIRI group,accompanied by mild hemorrhage and obvious infiltration of inflammatory cells.Neuronal cells underwent degeneration and necrosis,with sparse and disordered arrangement.The phenomena of nuclear condensation and nucleolus lysis were obvious.The Zea Longa score,cerebral infarction volume,brain tissue water content,levels of IL-1β,IL-18,ROS,MDA,and the expressions of GSDMD,TXNIP,nucleotide-binding oligomerization domain-like receptor protein 3(NLRP3),apoptosis-related punctate protein(ASC),and Caspase-1 increased,while the activities of SOD and GSH-Px decreased(P＜0.05).Compared with the CIRI group,the pathological damage of brain tissues in the SDF-L group and the SDF-H group was significantly improved.The Zea Longa score,cerebral infarction volume,brain tissue water content,levels of IL-1β,IL-18,ROS,MDA,and the expressions of GSDMD,TXNIP,NLRP3,ASC,and Caspase-1 decreased.The activities of SOD and GSH-Px increased(P＜0.05);TMAO treatment partially reversed the improvement effect of SDF on CIRI in rats.Conclusion SDF ameliorates cerebral CIRI in rats by inhibiting ROS/TXNIP pathway-mediated pyroptosis.

Background and purpose:Diffuse large B-cell lymphoma(DLBCL)is subclassified into germinal center B-cell-like(GCB)and non-GCB subtypes,which differ in prognosis and treatment response.However,current distinction still relies on invasive pathological assays.This study developed radiomics and deep-learning models based on multiparametric magnetic resonance imaging(MRI)to non-invasively differentiate the two subtypes preoperatively,thereby reducing dependence on histopathological examination.Methods:This study retrospectively included patients with pathologically confirmed DLBCL diagnosed at Huashan Hospital,Fudan University,and other institutions between March 2013 and December 2024.Using multiparametric MRI data,we developed DLBCL-subtype classification models that combined 4 radiomics-based machine-learning algorithms:support vector machine(SVM),logistic regression(LR),Gaussian process(GP)and Naive Bayes(NB),with 3 deep-learning architectures[densely-connected convolutional networks 121(DenseNet121),residual network 101(ResNet101)and EfficientNet-b5].Additionally,two radiologists with different experience levels independently classified DLBCL on MRI in a blinded fashion.Model and radiologist performance were quantified using the area under the receiver operating characteristic curve(AUC),accuracy(ACC),and F1-score to evaluate their ability to distinguish GCB from non-GCB subtypes.This study was approved by the Ethics Committee of Huashan Hospital of Fudan University(No.KY2024-663),and all patients signed informed consents.Results:A total of 173 patients were enrolled(55 with GCB subtype and 118 with non-GCB subtype).Radiomics and deep learning methods effectively distinguished DLBCL subtypes.Among these,the GP radiomics model(based on T1-CE+T2-FLAIR+ADC sequences)and DenseNet121 deep learning model(based on T1-CE+T2-FLAIR+ADC sequences)demonstrated optimal performance.Both achieved excellent results on the internal validation set(GP:AUC=0.900,ACC=0.896,F1=0.840;DenseNet121:AUC=0.846,ACC=0.854,F1=0.774)and maintained robustness on the external validation set.Furthermore,the classification efficacy of the optimal AI model surpassed that of experienced radiologists(highest physician AUC=0.678).Conclusion:Radiomics and deep-learning models based on multiparametric MRI features can effectively differentiate GCB from non-GCB subtypes of DLBCL.Among them,GP and DenseNet121 exhibit outstanding performance,especially when integrating multi-sequence feature sets for classifying DLBCL subtypes on complex imaging data.

Objective To propose a novel method for verifying the isocenter in radiotherapy based on markers and conduct a preliminary test. Methods A feasibility experiment was conducted on wooden box phantom for radiotherapy resetting. Fifteen groups of displacement data were randomly generated,corresponding to the position deviations of the isocenter in the radiotherapy plan relative to the original isocenter. According to each set of displacement data,with the aid of movable lasers and a CT scanning couch,CT scanning was performed with two sets of markers (3 per set) affixed to the phantom which were corresponding to the original and treatment isocenters,respectively. In the Eclipse treatment planning system,the coordinate data of the original and treatment isocenters were manually verified,and the difference of coordinate data was calculated to obtain the actual displacement value. The treatment isocenter position was finally confirmed by comparing with the actual displacement. In addition,the study attempts to use threshold segmentation algorithm to automatically detect metal markers and obtain coordinate values of the original isocenter on patient-positioned CT images. In the wooden box experiment,the absolute value of the difference between the actual displacement value and the planned displacement value (?d) was used to represent the position accuracy of treatment isocenter,and the deviation value obtained with threshold segmentation algorithm for isocenter detection was ?s. Results The ?d in the X (left-right),Y (superior-inferior) and Z (anterior-superior) directions was (0.83±0.37) mm,0 (0,0.5) mm and (0.45±0.29) mm,respectively. The ?s in the X,Y and Z directions was (0.46±0.22) mm,0 (0,0.5) mm and (0.33±0.29) mm,respectively. The mean values of ?s in 3 directions were all lower than 2 mm,within the range of permissible clinical positioning error. Conclusion The method of automatically verifying treatment isocenter position based on markers is feasible,and the study provides a useful reference for radiotherapy resetting using CT simulator.

Objective:To systematically evaluate the current status of research on the development of indicators for entrustable professional activities (EPAs) of residents in China.Methods:We searched the China National Knowledge Infrastructure, Wanfang Data, Airiti Library, PubMed, Embase, and Web of Science databases for literature on the development of EPA indicators for residents in China published between January 1, 2005 and February 28, 2025. Two researchers independently screened the literature and extracted data, followed by descriptive analysis. The quality of the studies was assessed using the Joanna Briggs Institute critical appraisal tool for expert opinion. Quantitative data were presented as medians (ranges) and qualitative data were presented as frequencies (percentages).Results:A total of eight articles were included, in which two general EPA indicator systems and six specialty-specific EPA indicator systems were developed for residents. The overall quality of the research was high, with the main shortcomings related to the methods used in the process of constructing the consensus indicators. The number of experts recruited ranged from 22 to 45, with 100.00% response rate, high authority coefficients (0.820-0.914), and high coordination coefficients (0.157-0.741). Most of the studies used literature reviews as one source for the indicator pool (8 studies, 100.00%), employed the Delphi method to reach consensus (6 studies, 75.00%), and provided inclusion criteria for the indicators (7 studies, 87.50%). However, only one study (12.50%) explored the practical application of the developed indicators, and none of the studies set indicator weights or conducted quality assessments. The number of EPA indicators developed ranged from 10 to 38 per study. The reporting of EPA indicators was included in most studies regarding titles (8 studies, 100.00%) and the expected levels of entrustment at various stages of training (6 studies, 75.00%), but the reporting on other aspects was lacking. Among the specialty-specific EPA indicators, 38.39% overlapped with the general EPAs indicators.Conclusions:The research on the development of EPA indicators for residents in China is still in its early stages, and there is room for improvement in methodological quality and reporting coverage. There is partial overlap between specialty-specific and general EPA indicators, failing to fully reflect the unique characteristics of different specialties.

Objective:To systematically evaluate the current status of research on the development of indicators for entrustable professional activities (EPAs) of residents in China.Methods:We searched the China National Knowledge Infrastructure, Wanfang Data, Airiti Library, PubMed, Embase, and Web of Science databases for literature on the development of EPA indicators for residents in China published between January 1, 2005 and February 28, 2025. Two researchers independently screened the literature and extracted data, followed by descriptive analysis. The quality of the studies was assessed using the Joanna Briggs Institute critical appraisal tool for expert opinion. Quantitative data were presented as medians (ranges) and qualitative data were presented as frequencies (percentages).Results:A total of eight articles were included, in which two general EPA indicator systems and six specialty-specific EPA indicator systems were developed for residents. The overall quality of the research was high, with the main shortcomings related to the methods used in the process of constructing the consensus indicators. The number of experts recruited ranged from 22 to 45, with 100.00% response rate, high authority coefficients (0.820-0.914), and high coordination coefficients (0.157-0.741). Most of the studies used literature reviews as one source for the indicator pool (8 studies, 100.00%), employed the Delphi method to reach consensus (6 studies, 75.00%), and provided inclusion criteria for the indicators (7 studies, 87.50%). However, only one study (12.50%) explored the practical application of the developed indicators, and none of the studies set indicator weights or conducted quality assessments. The number of EPA indicators developed ranged from 10 to 38 per study. The reporting of EPA indicators was included in most studies regarding titles (8 studies, 100.00%) and the expected levels of entrustment at various stages of training (6 studies, 75.00%), but the reporting on other aspects was lacking. Among the specialty-specific EPA indicators, 38.39% overlapped with the general EPAs indicators.Conclusions:The research on the development of EPA indicators for residents in China is still in its early stages, and there is room for improvement in methodological quality and reporting coverage. There is partial overlap between specialty-specific and general EPA indicators, failing to fully reflect the unique characteristics of different specialties.

Objective To investigate the relationship between serum glial fibrillary acidic protein(GFAP)level and transcranial Doppler(TCD)parameters in carotid stenosis patients after carotid stent implantation.Methods A total of 123 patients with carotid stenosis who received carotid stent implantation in our hospital from September 2021 to February 2024 were recruited,and di-vided into a normal group(39 cases)and a damaged group(84 cases)according to their cerebro-vascular reserve.The GFAP level and TCD parameters were collected before and after treatment.ROC curve analysis was employed to analyze the value of GFAP level in evaluating cerebrovascu-lar reserve in the patients.Results Significantly larger proportion of diabetes and higher level of total cholesterol were observed in the damaged group than the normal group(P＜0.05).Mean flow velocity(MFV),pulse index(PI),peak systolic velocity(PSV),and levels of GFAP,neuron-specific enolase(NSE)and S-100β were all obviously decreased in both groups after surgery than the levels before(P＜0.05).When compared with the normal group,the damaged group had nota-bly higher serum GFAP level before operation,and lower PI and PSV values and higher GFAP,NSE and S-100β levels after operation(P＜0.05,P＜0.01).Both pre-and post-operative serum GFAP levels were negatively correlated with postoperative MFV,PI and PSV(P＜0.01).The concomitant diabetes,pre-and post-operative serum GFAP levels,and postoperative PSV value and NSE and S-100β levels were independent influencing factors for cerebrovascular reserve in ca-rotid stenosis patients after carotid stent implantation(P＜0.05,P＜0.01).The post-operative se-rum GFAP level showed significantly better value than the pre-operative level in assessing cere-brovascular reserve,with an AUC value of 0.860(95％CI:0.786-0.916)and 0.777(95％CI:0.693-0.847),respectively.Conclusion Serum GFAP level is related to TCD parameters in ca-rotid stenosis patients after carotid stent implantation.Combined GFAP level and TCD parameters together can be used to evaluate the cerebrovascular reserve for the patients.

Background and purpose:Diffuse large B-cell lymphoma(DLBCL)is subclassified into germinal center B-cell-like(GCB)and non-GCB subtypes,which differ in prognosis and treatment response.However,current distinction still relies on invasive pathological assays.This study developed radiomics and deep-learning models based on multiparametric magnetic resonance imaging(MRI)to non-invasively differentiate the two subtypes preoperatively,thereby reducing dependence on histopathological examination.Methods:This study retrospectively included patients with pathologically confirmed DLBCL diagnosed at Huashan Hospital,Fudan University,and other institutions between March 2013 and December 2024.Using multiparametric MRI data,we developed DLBCL-subtype classification models that combined 4 radiomics-based machine-learning algorithms:support vector machine(SVM),logistic regression(LR),Gaussian process(GP)and Naive Bayes(NB),with 3 deep-learning architectures[densely-connected convolutional networks 121(DenseNet121),residual network 101(ResNet101)and EfficientNet-b5].Additionally,two radiologists with different experience levels independently classified DLBCL on MRI in a blinded fashion.Model and radiologist performance were quantified using the area under the receiver operating characteristic curve(AUC),accuracy(ACC),and F1-score to evaluate their ability to distinguish GCB from non-GCB subtypes.This study was approved by the Ethics Committee of Huashan Hospital of Fudan University(No.KY2024-663),and all patients signed informed consents.Results:A total of 173 patients were enrolled(55 with GCB subtype and 118 with non-GCB subtype).Radiomics and deep learning methods effectively distinguished DLBCL subtypes.Among these,the GP radiomics model(based on T1-CE+T2-FLAIR+ADC sequences)and DenseNet121 deep learning model(based on T1-CE+T2-FLAIR+ADC sequences)demonstrated optimal performance.Both achieved excellent results on the internal validation set(GP:AUC=0.900,ACC=0.896,F1=0.840;DenseNet121:AUC=0.846,ACC=0.854,F1=0.774)and maintained robustness on the external validation set.Furthermore,the classification efficacy of the optimal AI model surpassed that of experienced radiologists(highest physician AUC=0.678).Conclusion:Radiomics and deep-learning models based on multiparametric MRI features can effectively differentiate GCB from non-GCB subtypes of DLBCL.Among them,GP and DenseNet121 exhibit outstanding performance,especially when integrating multi-sequence feature sets for classifying DLBCL subtypes on complex imaging data.

Objective To propose a novel method for verifying the isocenter in radiotherapy based on markers and conduct a preliminary test. Methods A feasibility experiment was conducted on wooden box phantom for radiotherapy resetting. Fifteen groups of displacement data were randomly generated,corresponding to the position deviations of the isocenter in the radiotherapy plan relative to the original isocenter. According to each set of displacement data,with the aid of movable lasers and a CT scanning couch,CT scanning was performed with two sets of markers (3 per set) affixed to the phantom which were corresponding to the original and treatment isocenters,respectively. In the Eclipse treatment planning system,the coordinate data of the original and treatment isocenters were manually verified,and the difference of coordinate data was calculated to obtain the actual displacement value. The treatment isocenter position was finally confirmed by comparing with the actual displacement. In addition,the study attempts to use threshold segmentation algorithm to automatically detect metal markers and obtain coordinate values of the original isocenter on patient-positioned CT images. In the wooden box experiment,the absolute value of the difference between the actual displacement value and the planned displacement value (?d) was used to represent the position accuracy of treatment isocenter,and the deviation value obtained with threshold segmentation algorithm for isocenter detection was ?s. Results The ?d in the X (left-right),Y (superior-inferior) and Z (anterior-superior) directions was (0.83±0.37) mm,0 (0,0.5) mm and (0.45±0.29) mm,respectively. The ?s in the X,Y and Z directions was (0.46±0.22) mm,0 (0,0.5) mm and (0.33±0.29) mm,respectively. The mean values of ?s in 3 directions were all lower than 2 mm,within the range of permissible clinical positioning error. Conclusion The method of automatically verifying treatment isocenter position based on markers is feasible,and the study provides a useful reference for radiotherapy resetting using CT simulator.

Objective To investigate the molecular mechanism of ALKBH5 reducing sepsis-induced myocardial dysfunction(SIMD).Methods The expression levels of ALKBH5 and TRAF1 in the blood of 50 SIMD patients and 50 healthy individuals were detected using reverse transcription fluorescence quantitative polymerase chain reaction(RT-qPCR),and the correlation between their expression levels was analyzed by person analysis;In vitro experiments,H9C2 myocardial cells were divided into 7 groups according to over expression of TARF1 and knockdown ALKBH5.The molecular mechanism of ALKBH5 targeting TRAF1 to regulate lipopolysaccharide(LPS)induced myocardial cell damage was studied through experiments such as CCK8,ELISA,and Western blot;In the in vivo experiment of rats,LPS induced rats were divided into 6 groups according to over expression of TARF1 and knockdown ALKBH5.Experimental methods such as colorimetry,ELISA,Western blot,HE staining,and immuno-histochemistry were used to study the mechanism of ALKBH5 targeting TRAF1 through NF-κB pathway in reduc-ing myocardial cell damage.Results The expression levels of ALKBH5 and TRAF 1 were downregulated in SIMD,and the Pearson analysis showed a positive correlation between them(P<0.001);In vitro experiments showed that overexpression of TRAF1 promotes cell proliferation,inhibits the expression of inflammatory factors and proteins involved in the NF-κB pathway,and knockdown ALKBH5 obtain the opposite resulst;In vivo experi-ments in rats showed that knockdown ALKBH5 promotes injury in cardiomyocytes,expression of inflammatory factors and NF-κB-related pathway proteins,and nuclear translocation of NF-κB p65 protein,but the overexpression of TRAF 1 yielded the opposite results.Conclusion ALKBH5 increases the stability of TRAF1 by reducing its meth-ylation,thereby inhibiting NF-κB pathway,thereby reducing SIMD.